A Study of the Modified KDD 99 Dataset by Using Classifier Ensembles

Network security has been an important research area. KDD 99 dataset has been used to analyze various network security methods. However, it has been shown that this dataset has redundant data points that make the analysis bias for these data points. New modified data sets are proposed that overcome these weaknesses. The authors carried out the experiments with different classifiers on this datasets to study the applicability of different classification methods for this dataset. Na?ve Bayes and decision trees and their ensemble methods are used for this paper. They used different performance measures in their paper.